AICS - Artificial Intelligence for Cyber Security

The workshop will focus on the application of artificial intelligence (AI) to problems in cyber security. The emphasis will be on Internet of Things (IoT) and mobile devices relative to cyber security. The workshop will address technologies and their applications, such as machine learning, game theory, natural language processing, knowledge representation, automated and assistive reasoning, and human machine interactions. The workshop will emphasize cyber systems and research on techniques to enable resilience in mobile systems involving human-machine interactions.

IoT and mobile devices provide powerful sensing and computing capabilities to users and systems. These same capabilities, however, offer new opportunities for adversarial compromise, resulting in the loss of data and control, and could lead to infection spread to other connected devices. AI capabilities have the potential to help protect these mobile platforms in several ways. Because IoT mobile devices, such as smart phones, are often used by one individual at a time, behavioral analysis techniques that model normal user usage patterns can be leveraged to recognize anomalous, or out-of-the-ordinary, behaviors that might be indicative of misuse. In addition, graph analysis of a device’s connectivity network, such as a user’s social network or links in a web page, can be leveraged to identify malicious sites that could seek to infect the devices. Finally, AI capabilities that collect, correlate, and analyze multiple data sources at once can be leveraged to confirm the provenance and veracity of data from suspect IoT devices.

Addressing the cyber security challenges of IoT and mobile devices requires collaboration between several different research and development communities including the artificial intelligence, cyber-security, game theory, machine learning and formal reasoning communities.

The above applications of AI have the potential to impact cyber security in a positive way, bringing automated learning and game theory into the service of improved system resilience. Developing and applying these and other AI capabilities to cyber security problems requires collaboration between several different communities including the artificial intelligence, game theory, machine learning, and cyber-security communities, as well as the operational and commercial applications communities. This workshop is structured to encourage a lively exchange of ideas between researchers in these communities from the academic, public, and commercial sectors.

Workshop Topics

Topics of interest include, but are not limited to:

• Machine learning approaches to make cyber systems secure and resilient      
•        – Natural language processing techniques
•        – Anomaly/threat detection techniques
•        – Big Data noise reduction techniques
•        – Human behavioral modeling
• Formal reasoning, with focus on human element, in cyber systems
• Game Theoretic reasoning in cyber security
• Economics of cyber security
• Multi-agent interaction/agent-based modeling in cyber systems
• Modeling and simulation of cyber systems and system components
• Decision making under uncertainty in cyber systems
• Automated security aids for system administrators
• Quantitative human behavior models with application to cyber security
• Operational and commercial applications of AI

Challenge Problem (sponsored by Crowdstrike)
For information on this year’s AICS challenge problem: http://www-personal.umich.edu/~arunesh/AICS2018/

Workshop Format
Invited speakers, presentations, panel and group discussions

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome

One of two submissions is solicited:
• Full-length papers (up to 8 pages in AAAI format)
• Challenge problem papers (up to 8 pages in AAAI format)
Submissions are not anonymized. Please submit PDF via AICS Workshop website by November 3, 2018

Program Committee

• George Cybenko, Dartmouth College
• Robert Goldman, Smart Information Flow Technologies (SIFT)
• Christopher Kiekintveld, University of Texas at El Paso
• Robert Laddaga, Vanderbilt University
• Richard Lippmann, MIT Lincoln Laboratory
• Ranjeev Mittu, Naval Research Laboratory
• Sven Krasser, Crowdstrike
• Benjamin Rubinstein, University of Melbourne, Australia
• Milind Tambe, University of Southern California
• Robert Templeman, Navy Surface Warfare Center, Crane Division

Organizing committee

• William W. Streilein, MIT Lincoln Laboratory, MA, USA
• David R. Martinez, MIT Lincoln Laboratory, MA, USA
• Howard Shrobe, MIT/CSAIL, MA, USA
• Arunesh Sinha, University of Michigan, MI, USA
• Neal Wagner, MIT Lincoln Laboratory, MA, USA
• Cem Sahin, MIT Lincoln Laboratory, MA, USA  

Contact

All questions about submissions should be emailed to

Cynthia Devlin-Brooks
MIT Lincoln Laboratory
Email: Cynthia.Devlin-Brooks@ll.mit.edu
Voice: 781-981-7501
Fax: 781-981-4086